Ancillary techniques for neural network applications

M. A. El-Sharkawi, S. J. Huang

Research output: Contribution to conferencePaperpeer-review

22 Citations (Scopus)

Abstract

To a large extent, the successful implementation of neural nets depends on several ancillary techniques for data preprocessing, training and testing. Some of these techniques are investigated and discussed in this paper. They include genetic algorithm, fuzzy logic theory, query-based learning and feature extraction. For each technique, the paradigm, theory and application are described. The advantages of the application of these ancillary techniques for the neural networks are also listed. The simulation results for each proposed technique showed their significant role and practicality.

Original languageEnglish
Pages3724-3729
Number of pages6
DOIs
Publication statusPublished - 1994 Jan 1
EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
Duration: 1994 Jun 271994 Jun 29

Other

OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period94-06-2794-06-29

All Science Journal Classification (ASJC) codes

  • Software

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